DSpace Collection:
http://hdl.handle.net/2440/1095
2014-07-20T23:12:22ZLow-cost flow-rate estimate in separate layers along gas wells from temperature and pressure profiles
http://hdl.handle.net/2440/84061
Title: Low-cost flow-rate estimate in separate layers along gas wells from temperature and pressure profiles
Author: Barrett, Emile; Abbasy, Imran; Wu, C-R.; You, Zhenjiang; Bedrikovetski, Pavel
Abstract: Estimation of rate profile along the well is important information for reservoir characterisation since it allows distinction of the production rates from different layers. The temperature and pressure sensors in a well are small and inexpensive; while flow meters are cumbersome and expensive, and affect the flow in the well. The method presented in this peer-reviewed paper shows its significance in predicting the gas rate from temperature and pressure data. A mathematical model for pressure and temperature distributions along a gas well has been developed. Temperature and pressure profiles from nine well intervals in field A (Cooper Basin, Australia) have been matched with the mathematical model to determine the flow rates from different layers in the well. The presented model considers the variables as functions of thermal properties at each location, which is more accurate and robust than previous methods. The results of tuning the mathematical model to the field data show good agreement with the model prediction. Simple and robust explicit formulae are derived for the effective estimation of flow rate and thermal conductivity in gas wells. The proposed approach has been applied to determine the well gas rate and formation thermal conductivity from the acquired well pressure and temperature data in field A. It allows for recommending well stimulation of layers with low production rates.2012-12-31T13:30:00ZOptimisation and economical evaluation of infill drilling in CSG reservoirs using a multi-objective genetic algorithm
http://hdl.handle.net/2440/84060
Title: Optimisation and economical evaluation of infill drilling in CSG reservoirs using a multi-objective genetic algorithm
Author: Salmachi, Alireza; Sayyafzadeh, Mohammad; Haghighi, Manouchehr
Abstract: Water production in the early life of Coal Seam Gas (CSG) recovery makes these reservoirs different from conventional gas reservoirs. Normally, a large amount of water is produced during the early production period, while the gas-rate is negligible. It is essential to drill infill wells in optimum locations to reduce the water production and increase the gas recovery. To optimise infill locations in a CSG reservoir, an integrated framework is developed to couple the reservoir flow simulator (ECLIPSE) and the genetic algorithm (GA) optimisation toolbox of (MATLAB). In this study, the desired objective function is the NPV of the infill drilling. To obtain the economics of the infill drilling project, the objective function is split into two objectives. The first objective is the gas income; the second objective is the cost associated with water production. The optimisation problem is then solved using the multi-objective solver. The economics of the infill drilling program is investigated for a case study constructed based on the available data from the Tiffany unit in San Juan basin when gas price and water treatment cost are variable. Best obtained optimal locations of 20 new wells in the reservoir are attained using this optimisation framework to maximise the profit of this project. The results indicate that when the gas price is less than $2/Mscf, the infill plan, regardless of the cost of water treatment, is not economical and drilling additional wells cannot be economically justified. When the cost of water treatment and disposal increases from $0.01/STB to $4/STB, the optimisation framework intelligently distributes the infill wells across the reservoir in a way that the total water production of infill wells is reduced by 26%. Simulation results also indicate that when water treatment is an expensive operation, lower water production is attained by placing the infill wells in depleted sections of the coal bed, close to the existing wells. When water treatment cost is low, however, infill wells are freely allocated in virgin sections of the coal bed, where both coal gas content and reservoir pressure are high.2012-12-31T13:30:00ZPresent-day in-situ stresses versus paleo-stresses for locating sweet spots in unconventional reservoirs
http://hdl.handle.net/2440/84001
Title: Present-day in-situ stresses versus paleo-stresses for locating sweet spots in unconventional reservoirs
Author: Abul Khair, Hani Farouq; Cooke, Dennis; Hand, Martin Phillip
Abstract: The effect of stresses on permeability is a combination of external stress and pore pressure. The authors examine if and how present-day in-situ stresses and the spatial distribution of permeable locations in the Moomba-Big Lake fields in the Cooper Basin are correlated. Image logs, well logs, and formation tests are analysed and the orientation and magnitudes of the three principal stresses are calculated. A 3D model was constructed and the calculated stress magnitudes and orientations were applied to the model using the software Poly3D. The resulting stress distribution in the present-day stress state showed a potential sweet spot in the Big Lake field, which is presently the location of a gas pool that forms, with the Moomba field, one-third of the gas reserve in SA. No potential sweet spots, however, are located in the Moomba area. The authors also used the finite element method (FEM) and the boundary element method (BEM) for modelling the behaviour of folds, fractures, and faults and for mimicking the tectonic history of the basin. Software codes Dynel3D and Traptester were used to examine the validity of geomechanical restoration techniques for locating sweet spots in the Moomba-Big Lake fields. The methodology attempts to reconstruct the present-day structural and geometrical placement and to predict fractures generated due to stresses released during past tectonic events. Predicted stresses succeeded in mapping the same sweet spot in the Big Lake field using both software codes. Accordingly, the present permeability and production rate is controlled by a combination of present-day and stored stresses.2012-12-31T13:30:00ZAssessment of different model-management techniques in history matching problems for reservoir modelling
http://hdl.handle.net/2440/83977
Title: Assessment of different model-management techniques in history matching problems for reservoir modelling
Author: Sayyafzadeh, Mohammad; Haghighi, Manouchehr
Abstract: History matching is a computationally expensive inverse problem. The computation costs are dominantly associated with the optimisation step. Fitness approximation (proxy-modelling) approaches are common methods for reducing computational costs where the time-consuming original fitness function is substituted with an undemanding function known as approximation function (proxy). Almost all of the applied fitness approximation methods in history-matching problems use a similar approach called uncontrolled fitness approximation. It has been corroborated that the uncontrolled fitness approximation approach may mislead the optimisation direction to a wrong optimum point. To prevent this error, it is endorsed that the original function should be utilised along with the approximation function during the optimisation process. To make use of the original function efficiently, a modelmanagement (evolution-control) technique should be applied. There are three different techniques: individual-based, population- based, and adaptive. By using each of these techniques, a controlled fitness approximation approach is assembled, which benefits from online learning. In the first two techniques, the number of original function evaluations in each evolutioncontrol cycle is fixed and predefined, which may result in an inefficient model management. In the adaptive technique, the number is altered based on the fidelity of the approximation function. In this study, a specific adaptive technique is designed, based on heuristic fuzzy roles; then, for the first time, the applications of all the three techniques are investigated in history matching. To deliver an assessment between the four approaches (the uncontrolled approach and three controlled approaches), a framework is developed in which ECLIPSE-E100 is coupled with MATLAB; and an artificial neural network, a genetic algorithmâ€” with a customised crossoverâ€”and a Latin hypercube sampling strategy are used as the proxy model, optimiser, and experimental design method, respectively. History matching is carried out using each of the four approaches for the PUNQS3 reservoir model, while the same amount of computation time was allowed for each of the approaches. The outcomes demonstrate that the uncontrolled approach cannot deliver reliable results in comparison with the controlled approaches, and among the controlled approaches, the developed adaptive technique is more efficient.2012-12-31T13:30:00Z